Update app.py

app.py

@@ -4,11 +4,11 @@ import torch
 import re
 
 # Load model and tokenizer
-model_name = "microsoft/DialoGPT-medium"
+model_name = "microsoft/DialoGPT-small"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 tokenizer.pad_token = tokenizer.eos_token
 model = AutoModelForCausalLM.from_pretrained(model_name)
-model.config.pad_token_id = tokenizer.eos_token_id  # Ensure no pad token issues
+model.config.pad_token_id = tokenizer.eos_token_id
 
 # System prompt for company context
 SYSTEM_PROMPT = """You are MediaDecode's AI assistant, a professional IT services and software development company. 
@@ -35,23 +35,36 @@ DEFAULT_RESPONSE = """🤖 I couldn't find a specific answer. For detailed inqui
 - Email: info@mediadecode.com
 - Visit: [Support Page](https://mediadecode.com/contact)"""
 
-# Response generator
 def respond(message, chat_history):
+    # Clean the input message
+    message = message.strip().lower()
+    
+    # Check for empty message
+    if not message:
+        return "Please enter a valid question or query."
+    
+    # Check for greeting
+    if any(greeting in message for greeting in ["hi", "hello", "hey"]):
+        return "Hello! Welcome to MediaDecode support. How can I help you today?"
+    
     # Check for predefined FAQs
     for pattern, response in FAQ_RESPONSES.items():
         if re.search(pattern, message):
-            return f"{response}\n\nHow else can I help?"
+            return response
 
     # Generate AI response
     prompt = f"{SYSTEM_PROMPT}\nUser: {message}\nAI:"
-    inputs = tokenizer(prompt, return_tensors="pt")
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
+    
     with torch.no_grad():
         outputs = model.generate(
             inputs.input_ids,
             max_length=200,
             pad_token_id=tokenizer.eos_token_id,
-            temperature=0.7
+            temperature=0.7,
+            do_sample=True
         )
+    
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     response = response.split("AI:")[-1].strip()
 
@@ -69,7 +82,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     *Powered by AI + Company Knowledge Base*
     """)
 
-    chatbot = gr.Chatbot(height=400)
+    chatbot = gr.Chatbot(height=400, label="Chat History")
     msg = gr.Textbox(label="Your Query", placeholder="e.g., What's your pricing for Java development?")
     clear = gr.Button("Clear Chat")
 
@@ -77,16 +90,15 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         return "", history + [[user_message, None]]
 
     def bot(history):
-        if not history or not history[-1][0]:
-            return history
-        bot_reply = respond(history[-1][0], history[:-1])
-        history[-1][1] = bot_reply
+        user_message = history[-1][0]
+        bot_response = respond(user_message, history[:-1])
+        history[-1][1] = bot_response
         return history
 
-    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+    msg.submit(user, [msg, chatbot], [msg, chatbot]).then(
         bot, chatbot, chatbot
     )
 
-    clear.click(lambda: [], None, chatbot, queue=False)
+    clear.click(lambda: None, None, chatbot, queue=False)
 
-demo.launch()
+demo.launch()